Jeremy Kawahara

Applying machine and deep learning to analyze medical images

 (xxx) xxx - xxxx 


Vancouver, BC, Postal Code, Canada


PhD student in Computing  Machine learning in medical images

Simon Fraser University / Computing Science

September 2013 - Present, Burnaby, Canada

Ph.D. student in Computing Science                                    

September 2011 - September 2013, Burnaby, Canada

M.Sc. in Computing Science                                                    

Vancouver Island University / Computing Science

2011, Nanaimo, Canada

B.Sc. in Computing Science, with Distinction


Image analysis Researcher  Sole proprietor  Gov't contractor  Tutor

Medical Image Analysis Lab

Medical Image Analysis Lab / Research Assistant

September 2011 - Present, Burnaby, Canada

Research includes classification of: skin diseased images, tumors in ultrasound video, spinal cord in MRI, and clinical disability in multiple sclerosis patients. / Image Analysis Researcher

September 2014 - February 2015 , Vancouver, Canada

Developed an image-based art recommendation and colour search system

Qatar Robotic Surgery Centre / Research Assistant

September 2013 - September 2014, Doha, Qatar & Burnaby, Canada

Classified tumor in ultrasound video during image guided robotic kidney surgeries

Simon Fraser University / Teaching Assistant

September 2011 - April 2014 (4 semesters), Burnaby, Canada

CMPT 128: Intro to Computing Science for Engineering Students

CMPT 376: Writing for Computer Scientists; CMPT 340: Biomedical Computing

Kawahara Innovations / Owner & Developer

2010 - 2013, Nanaimo/Burnaby, Canada

Developed data-entry desktop software to track fishing/hunting activities, defined project requirements, and business aspects (invoicing, contracts, sub-contractors)

Vancouver Island Disability Services / Peer Tutor

2009 - 2010, Nanaimo, Canada

Tutored students with learning disabilities Computing courses

Fisheries and Oceans Canada / Software Developer

2008 - 2010, Nanaimo, Canada

Implemented systems to organize, report, and internationally share otolith thermal mark information. Provided training, support, maintenance, and documentation.


Skin Diseases  Melanoma  Connectome  Ultrasound MRI  Multiple Sclerosis

J. Kawahara, K. P. Moriarty, and G. Hamarneh, "Graph Geodesics to Find Progressively Similar Skin Lesion Images". In MICCAI-GRAIL, 2017. (oral presentation)

J. Kawahara, C. J. Brown, S. P. Miller, B. G. Booth, V. Chau, R. E. Grunau, J. G. Zwicker, G. Hamarneh, "BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment." NeuroImage, 2017 (journal)

J. Kawahara, A. BenTaieb, and G. Hamarneh, “Deep Features to Classify Skin Lesions,” IEEE ISBI, 2016. (oral presentation, runner-up for best student paper)

J. Kawahara, and G. Hamarneh, "Multi-Resolution-Tract CNN with Hybrid Pretrained and Skin-Lesion Trained Layers". In MICCAI-MLMI, 2016. (oral presentation) 

A. BenTaieb, J. Kawahara, and G. Hamarneh, “Multi-loss Convolutional Networks for Gland Analysis in Microscopy,” in IEEE ISBI, 2016. (oral presentation)

J. Kawahara, G. Hamarneh, “Image Content-Based Navigation of Skin Conditions.” World Congress of Dermatology, 2015 (abstract, poster presentation)

tumorous frames

J. Kawahara, J.-M. Peyrat, O. Al-Alao, R. Abugharbieh, and G. Hamarneh, “Auto-

matic Labelling of Tumourous vs Tumour-Free Frames in Free-Hand Laparoscopic Ul-

trasound Video,” in MICCAI, 2014. (poster presentation). 

J. Kawahara, C. McIntosh, R. Tam, and G. Hamarneh, “Novel morphological and appearance features for predicting physical disability from MR images in multiple sclerosis patients,” in MICCAI CSI Workshop, Springer, 2014. (oral presentation). 

G. Hamarneh, A. Amir-Khalili, M. Nosrati, I. Figueroa, J. Kawahara, O. Al-Alao, J.-M. Peyrat, J. Abi-Nahed, A. Al-Ansari, and R. Abugharbieh, “Towards multi-modal image-

guided tumour identification in robot-assisted partial nephrectomy,” in IEEE MECBME, 2014.

J. Kawahara, C. McIntosh, R. Tam, and G. Hamarneh, “Augmenting auto-context with global geometric features for spinal cord segmentation,” MICCAI MLMI Workshop, 2013. (poster).


J. Kawahara, C. McIntosh, R. Tam, and G. Hamarneh, “Globally optimal spinal cord segmentation using a minimal path in high dimensions,” in IEEE ISBI, 2013. (poster). 

Master's Thesis       


Title: Spinal cord segmentation and disability prediction in multiple sclerosis using novel optimization and machine learning methods 

Supervisors: Dr. Ghassan Hamarneh, Dr. Roger Tam, Dr. Chris McIntosh

Bachelor’s Research Project

Title: Development of Computer Aided Annuli Detection Software

Supervisor: Dr. Huizhu Liu

Description: Predicted the age of chum salmon scales from images of the scales.

 Scholarships and Awards

2017 Graduate Prize - Top Grad Student in Computing Science, July, SFU, (Institutional)

2017 DBMiner Graduate Scholarship, July, Simon Fraser University, (Institutional Comp.)

2017 FAS Graduate Fellowship, May 2017, Simon Fraser University, (Institutional Comp.)

2017 Graduate Fellowship, Jan 2017, Simon Fraser University, (Institutional Competition)

2016 Best Student Paper - Runner Up, IEEE ISBI, (International Competition)

2016 FAS Graduate Fellowship, May 2016, Simon Fraser University, (Institutional Comp.)

2016 Helmut and Hugo Eppich Fam GS, Jan 2016, (Institutional Competition)

2015 Graduate Fellowship, Jan 2015, Simon Fraser University, (Institutional Competition)

2015 Borden Ladner Gervais Graduate Scholarship, Jan 2015, (Institutional Competition)

2014 NSERC PGS D, 3 year funding, Sept 05th 2014, NSERC, (National Competition)

2014 MICCAI Society Student Travel Award, May 23rd 2014, (International Competition)

2013 Travel and Minor Research Award, October 28th 2013, Simon Fraser University

2013 Travel and Minor Research Award, March 15th 2013, Simon Fraser University

 Technical and Research Interests

Tools [experience]:

[Basic]: C/C++, Java, Javascript,  PHP, R, VB.NET,

[Intermediate]: Caffe, database design, MATLAB, Oracle DB, PL/SQL, TensorFlow

Current Tools:

google-app-engine, HTML/CSS, Keras, LaTeX, Python 

Research Interests:

Medical image analysis, machine/deep learning

Invited Talks

Canadian Neurosurgical Innovation Meeting / Guest Speaker

On behalf of Dr. Ghassan Hamarneh

Computer Vision and Machine Learning for Medical Image Analysis, (Sept 2017)

University of British Columbia / Guest Lecturer

BMEG 410/510 - Biomedical Equipment, Physiology, and Anatomy, (Sept. 2017)
BMEG 410/501 - Biomedical Equipment, Physiology, and Anatomy, (Nov. 2016)

Simon Fraser University / Guest Lecturer

CMPT 310 - Artificial Intelligence Survey, (July 2016)

 Group Affiliations

Medical Image Analysis Lab

Medical Image Analysis Lab, Burnaby, BC, Canada

Sept 2011 - present 

Elected council representative for SFU’s Computing Science graduate students

Jan 2013 - Sept 2015

Image Guided Robotic Surgery, Doha, Qatar

Sept 2013 - Sept 2014 

Toastmasters International, Nanaimo, BC, Canada

Sept 2010 - Aug 2011

Other Interests

Audiobooks   Google Scholar Profile   GitHub-Mark.png

Last updated: October 6, 2017

Online resume available: